{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_diabetes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ld = load_diabetes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.03807591  0.05068012  0.06169621 ... -0.00259226  0.01990842\n",
      "  -0.01764613]\n",
      " [-0.00188202 -0.04464164 -0.05147406 ... -0.03949338 -0.06832974\n",
      "  -0.09220405]\n",
      " [ 0.08529891  0.05068012  0.04445121 ... -0.00259226  0.00286377\n",
      "  -0.02593034]\n",
      " ...\n",
      " [ 0.04170844  0.05068012 -0.01590626 ... -0.01107952 -0.04687948\n",
      "   0.01549073]\n",
      " [-0.04547248 -0.04464164  0.03906215 ...  0.02655962  0.04452837\n",
      "  -0.02593034]\n",
      " [-0.04547248 -0.04464164 -0.0730303  ... -0.03949338 -0.00421986\n",
      "   0.00306441]]\n"
     ]
    }
   ],
   "source": [
    "print(ld.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(ld.target)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 "nbformat": 4,
 "nbformat_minor": 2
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